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Enhanced Bioenergy Production through Integration of Molecular Biotechnology and Bioprocess Technology Approaches
Get PDF九州工業大学博士学位論文 学位記番号:生工博甲第209号 学位授与年月日:平成25年9月27日Chapter1 General overview and big picture||Chapter2 Uncharacterized Genes in Escherichia coli Related to Biohydrogen Production||Chapter3 Uncharacterized Escherichia coli Proteins YdjA and YhjY Related to Biohydrogen Production||Chapter4 Metabolic Engineering to Enhance Hydrogen Production Using YhjY in Escherichia Coli||Chapter5 The curiosity a cryptic function of pseudogene in Escherichia coli genome towards hydrogen production||Chapter6 Electricity Generation from Waste Activated Sludge Using Microbial Fuel Cells Application||Chapter7 Influence of Pretreated Activated Sludge for Electricity Generation in Microbial Fuel Cell Application||Chapter8 Exclusive conclusion and suggestio
Holonomic Omnidirectional Vehicle with Ball Wheel Drive Mechanism
No full text九州工業大学博士学位論文 学位記番号:生工博甲第202号 学位授与年月日:平成25年3月25日第1章 研究の背景と目的||第2章 球体駆動式全方向移動機構の開発||第3章 歩行訓練支援ロボットの開発||第4章 全方向電動車いすの開発||第5章 全方向衝突検知装置の開発||第6章 結
消失点発見とテクスチャオリエンテーション算出による進路エリア検出
No full text九州工業大学博士学位論文 学位記番号:情工博甲第277号 学位授与年月日:平成25年3月25日1 Introduction||2 Vanishing point detection||3 Road area extraction||4 ConclusionsRoad area extraction plays an important role in different areas of computer vision such as autonomous driving, car collision warning and pedestrian crossing detection. Detecting road areas from a single road image is a challenging problem as the detection algorithm must be able to deal with continuously changing backgrounds, different environment (urban, high ways, off-road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Over the past few decades, numerous road area extraction methods have been widely published for urban and highway roads, structured roads, and unstructured roads. In all of these studies, estimating a location of vanishing point (VP) is a key requirement. A set of parallel lines in the world space by perspective projection converges to a common point in image space known as the VP. If the VP can be located correctly, then it is more likely to detect the road area properly. State-of-the-art VP-based road detection methods can be mainly grouped into three categories: edge-based methods, prior-based methods, and texture-based methods. Most edgebased methods take advantage of computational efficiency, and they can be applied to real time systems. However, the disadvantage is that they only work well for structured roads with clear painted lines or distinct road boundaries, while they usually fail in unstructured roads lacking sharply defined, smoothly curving edge. In order to overcome the limitation of these edge-based methods, prior-based methods and texture-based methods for road detection have been widely proposed. Most prior-based methods are robust to varying imaging conditions, road types and sur-rounding environments. However, they often require a large-scale image or video training database and also manual works for labeling VPs for the training stage. Hence, such prior-based methods are inapplicable to detect the road region from a single road image. In contrast, texture-based methods are very effective at detecting road areas for both structured roads and unstructured roads. These methods first search for local oriented textures and then make them vote for the location of the roads VP. In order to segment the road area, a VP-constrained group of dominant edges are detected, and two most dominant edges are selected as the road borders. In general, the disadvantages of these texture-based methods are: i) the computational cost of VP detection process is high, and ii) an estimation error of VP detection which may affect the performance of road area extraction is obtained in some images. In this thesis, our main objectives are: i) to reduce the computational cost and improve the performance of VP detection algorithm, and ii) to propose a new VP-based road area extraction method from a single road image. For this purpose, this thesis has been divided into four chapters. In Chapter 1, the background and some related works are introduced. Chapter 2 is in accordance with the first objective mentioned above. In this chapter, our novel texture-based local soft voting method for VP detection is explained. Firstly, Gabor filters and confidence level function are introduced. Gabor filters are used to calculate the texture orientation at every pixel of the road image, and the confidence level function is used to determine the remaining voters which are useful for the VP voting process by checking the reliability of the obtained texture orientations. After that, a novel local soft voting method is proposed, in which the number of scanning pixels is much reduced to reduce the computational cost, and a new VP candidate region is introduced to improve the estimation accuracy. The proposed VP detection method has been implemented and tested on 1000 road images which contain large variations in color, texture, lighting condition and surrounding environment. The experimental results demonstrate that this new voting method is both efficient and effective in detecting the VP from a single road image and requires much less computational time when compared to a previous voting method. Chapter 3 is in accordance with the second objective stated above. In this chapter, our new VP-constrained road area extraction method is described. The goal of this method is to detect the most immediate straight road part in the direction of the optical axis of the forwarding looking cameras based on estimating two lines (road boundaries) going from the VP and below the VP in the road image. In this method, in order to achieve a one degree level of precision for road boundaries detection, a histogram of 180 angles corresponding to angles of 180 lines going from the detected VP is used. When generating the histogram, the color information of the road image is combined to improve the estimation performance. The proposed road area extraction method has been implemented and tested on 1000 road images which are same as ones used in Chapter 2. The experimental results show that our proposed method performs well in challenging conditions. Finally, Chapter 4 presents our conclusions and future work
No full textFish can see not only the visible rays of light for human being but also the ultraviolet rays. However, the effects of the ultraviolet rays on the fish behavior have not been investigated. It is known that the reaction of fish against the reflected light and transmitted light is different irrespective of the same species. In this study, the effects of the reflected ultraviolet light and transmitted ultraviolet light on the fish behavior were investigated experimentally. It was found that the reflected ultraviolet light by the side and bed wall has no effect on the fish behavior. In contrast, the ayu swims under the irradiated area of ultraviolet light by ch
Supramolecular Assembly for Electrochemical Gene Detection
No full text電気化学を利用した遺伝子検出法は，簡便かつ迅速な測定法を提供できるとともに装置のコンパクト化が容易であるという理由から注目されている．電気化学的デオキシリボ核酸（DNA）検出試薬として開発したフェロセン化ナフタレンジイミド（FND）は2本鎖DNAと縫い込み型で結合し，シュードカテナン構造を形成することによって，2本鎖DNAと安定な複合体を形成する．この性質をプローブDNA固定化電極と組み合わせることによって目的遺伝子の電気化学的検出に成功した．FNDまたはその誘導体を用いた電気化学的遺伝子検出のさらなる高性能化を図るために，超分子形成可能なFND誘導体を新たに構築した．ここでは，これまで報告してきた超分子形成を利用したDNAまたはDNA関連酵素の電気化学的検出技術について報告する
Study on the Method of Constructing a Statistical Shape Model and Its Application to the Segmentation of Internal Organs in Medical Images
Get PDF九州工業大学博士学位論文 学位記番号:工博甲第353号 学位授与年月日:平成25年9月27日Chapter 1: Introduction||Chapter 2: Framework of Medical Image Segmentation||Chapter 3: 2-D Organic Regions Using Active Shape Model and Genetic Algorithm||Chapter 4: Alignment of 3-D Models||Chapter 5: Corespondence of 3-D Models||Chapter 6:Experiments of Organic Segmentation||Chapter 7: Visualization Technology and Its Applications||Chapter 8: Conclusions and Future WorksIn image processing, segmentation is one of the critical tasks for diagnostic analysis and image interpretation. In the following thesis, we describe the investigation of three problems related to the segmentation algorithms for medical images: Active shape model algorithm, 3-dimensional (3-D) statistical shape model building and organic segmentation experiments. For the development of Active shape models, the constraints of statistical model reduced this algorithm to be difficult for various biological shapes. To overcome the coupling of parameters in the original algorithm, in this thesis, the genetic algorithm is introduced to relax the shape limitation. How to construct a robust and effective 3-D point model is still a key step in statistical shape models. Generally the shape information is obtained from manually segmented voxel data. In this thesis, a two-step procedure for generating these models was designed. After transformed the voxel data to triangular polygonal data, in the first step, attitudes of these interesting objects are aligned according their surface features. We propose to reflect the surface orientations by means of their Gauss maps. As well the Gauss maps are mapped to a complex plane using stereographic projection approach. The experiment was run to align a set of left lung models. The second step is identifying the positions of landmarks on polygonal surfaces. This is solved by surface parameterization method. We proposed two simplex methods to correspond the landmarks. A semi-automatic method attempts to “copy” the phasic positions of pre-placed landmarks to all the surfaces, which have been mapped to the same parameterization domain. Another automatic corresponding method attempts to place the landmarks equidistantly. Finally, the goodness experiments were performed to measure the difference to manually corresponded results. And we also compared the affection to correspondence when using different surface mapping methods. The third part of this thesis is applying the segmentation algorithms to solve clinical problems. We did not stick to the model-based methods but choose the suitable one or their complex according to the objects. In the experiment of lung regions segmentation which includes pulmonary nodules, we propose a complementary region growing method to deal with the unpredictable variation of image densities of lesion regions. In the experiments of liver regions, instead of using region growing method in 3-D style, we turn into a slice-by-slice style in order to reduce the overflows. The image intensity of cardiac regions is distinguishable from lung regions in CT image. But as to the adjacent zone of heart and liver boundary are generally blurry. We utilized a shape model guided method to refine the segmentation results.3-D segmentation techniques have been applied widely not only in medical imaging fields, but also in machine vision, computer graphic. At the last part of this thesis, we resume some interesting topics such as 3-D visualization for medical interpretation, human face recognition and object grasping robot etc
無機塩類に対するウシガエル味神経応答の高浸透圧による修飾
Get PDF九州工業大学博士学位論文 学位記番号:生工博甲第211号 学位授与年月日:平成25年9月27日1 研究背景||2 味神経応答に対する浸透圧の作用||3 展望と結